Update app.py

app.py

@@ -81,17 +81,73 @@ with ui.navset_card_tab(id="tab"):
         with ui.layout_columns():
             with ui.card():
                 ui.input_selectize("virus_selector_1", "Select your viruses:", virus_new, multiple=True, selected=None)
+                        # with ui.card():
+                ui.input_selectize(
+                    "plot_type_distro",
+                    "Select your distrobution variance view:",
+                    ["Variance across bp", "Standard deviation across bp", "Full Genome Distrobution"],
+                    multiple=False,
+                    selected="Full Genome Distrobution",
+                )
+                
 
         @render.plot()
         def plot_distro_new():
             import seaborn as sns 
-            df = MASTER_DF[MASTER_DF["organism_name"].isin(input.virus_selector_1())].copy()
-            df = df.explode('charts').copy()
-            ax = sns.histplot(data=df, x='charts', hue='organism_name', stat='density')  
-            ax.set_title("Distribution")
-            ax.set_xlabel("Distance from mean")
-            ax.set_ylabel("Density")
-            return ax
+            plot_type = input.plot_type_distro()
+            if plot_type == "Full Genome Distrobution":
+                df = MASTER_DF[MASTER_DF["organism_name"].isin(input.virus_selector_1())].copy()
+                df = df.explode('charts').copy()
+                ax = sns.histplot(data=df, x='charts', hue='organism_name', stat='density')  
+                ax.set_title("Distribution")
+                ax.set_xlabel("Distance from mean")
+                ax.set_ylabel("Density")
+                return ax
+            elif plot_type == "Standard deviation across bp":
+                df = MASTER_DF[MASTER_DF["organism_name"].isin(input.virus_selector_1())].copy()
+                dfs = []
+                for organism in input.virus_selector_1():
+                        df_tiny = df[df['organism_name'] == organism].copy()
+                        y = df_tiny['std'].values[0].tolist()
+                        x = [x for x in range(len(y))]
+                        df_tiny = pd.DataFrame()
+        
+                        df_tiny['y'] = y
+                        df_tiny['x'] = x
+                        df_tiny['organism'] = organism
+                        dfs.append(df_tiny)
+                
+                df_k = pd.DataFrame()
+                df_k = pd.concat(dfs)
+                df_k = df_k.explode(column =['x', 'y']).copy()
+                ax = sns.lineplot(data=df_k, x='x',y = 'y', hue='organism')   
+                ax.set_title("Standard Deviation across basepairs")
+                ax.set_xlabel("Basepair")
+                ax.set_ylabel("Std")
+                
+                return ax
+            elif plot_type == "Variance across bp":
+                df = MASTER_DF[MASTER_DF["organism_name"].isin(input.virus_selector_1())].copy()
+                dfs = []
+                for organism in input.virus_selector_1():
+                        df_tiny = df[df['organism_name'] == organism].copy()
+                        y = df_tiny['var'].values[0].tolist()
+                        x = [x for x in range(len(y))]
+                        df_tiny = pd.DataFrame()
+        
+                        df_tiny['y'] = y
+                        df_tiny['x'] = x
+                        df_tiny['organism'] = organism
+                        dfs.append(df_tiny)
+                
+                df_k = pd.DataFrame()
+                df_k = pd.concat(dfs)
+                df_k = df_k.explode(column =['x', 'y']).copy()
+                ax = sns.lineplot(data=df_k, x='x',y = 'y', hue='organism')   
+                ax.set_title("Variance across basepairs")
+                ax.set_xlabel("Basepair")
+                ax.set_ylabel("Variance")
+                return ax
 
     with ui.nav_panel("Viral Microstructure"):
         ui.panel_title("Kmer Distribution")